Lead AI Architect

About the role

Cigna Healthcare is looking for a Lead AI Architect to define, adopt and assure AI-enabled data architectures that are commercially viable, technically robust and aligned with Cigna's enterprise and data strategy. Reporting to the International Health Global Architecture function, the role sets architectural direction and works with business leaders, product teams, engineering and third-party partners to deliver data and AI solutions that meet regulatory, operational and security requirements.

Key responsibilities

• Architect and own enterprise-scale Generative AI platforms for internal pilots, automation assistants, knowledge discovery and customer-facing AI experiences, including LLM-based applications, model access, orchestration, retrieval, prompt management, evaluation and observability.
• Define reference architectures and design patterns for AI model lifecycle management, pipelines, feature engineering and data platforms, and advise senior leadership on AI strategy and adoption.
• Take part in the full delivery lifecycle, from concept and investment cases through design assurance and governance, including design reviews, standards and risk management.
• Engage with business, IT and third-party partners, lead the assessment of third-party data and AI solutions and apply commercial awareness in architectural decisions.
• Mentor architects, designers and developers and contribute to the maturity of Cigna's data and AI architecture capability.

Required profile

• Advanced degree in Computer Science, Artificial Intelligence, Machine Learning or a related field.
• 10+ years of experience building and architecting large-scale software or AI systems in medium-to-large enterprises.
• 5+ years of experience with AI/ML, NLP or Generative AI.
• Experience in regulated or compliance-sensitive environments such as healthcare, finance or insurance.
• Ability to influence technical and non-technical stakeholders, with English at C2 level.

Required skills

• Generative AI: LLMs, embeddings, RAG, knowledge bases, multimodal embeddings, agentic workflows and MCP concepts.
• AI gateway and model access layer design, vector databases and semantic search.
• Document intelligence platforms (Azure Form Recognizer, AWS Textract, Google Document AI) and Intelligent Document Processing.
• Workflow orchestration frameworks such as LangChain or LangGraph, OCR, NLP and entity linking.
• AI governance, model lifecycle and responsible use of data and AI.

What we offer

• Competitive salary.
• Multicultural and hybrid working environment.
• Private medical insurance and employee wellbeing benefits.
• Educational development program.